{
 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "学习目标\n",
    "- 会使用Seaborn绘制箱线图、小提琴图\n",
    "- 会使用Seaborn绘制条形图、点图"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "cc041964dafff128"
  },
  {
   "cell_type": "markdown",
   "source": [
    "数据集中的数据类型有很多种，除了连续的特征变量之外，最常见的就是类别型的数据了，比如人的性别、学历、爱好等，这些数据类型都不能用连续的变量来表示，而是用分类的数据来表示。\n",
    "\n",
    "Seaborn针对分类数据提供了专门的可视化函数，这些函数大致可以分为如下三种:\n",
    "\n",
    "- 分类数据散点图: swarmplot()与 stripplot()。\n",
    "- 类数据的分布图: boxplot() 与 violinplot()。\n",
    "- 分类数据的统计估算图:barplot() 与 pointplot()。\n",
    "下面两节将针对分类数据可绘制的图形进行简单介绍，具体内容如下\n",
    "# 1 类别散点图\n",
    "通过 stripplot()函数可以画一个散点图， stripplot0函数的语法格式如下。\n",
    "```python\n",
    "seaborn.stripplot(x=None, y=None, hue=None, data=None, order=None, hue_order=None, jitter=False)\n",
    "```\n",
    "上述函数中常用参数的含义如下\n",
    "\n",
    "- (1) x，y，hue：用于绘制数据的输入。\n",
    "- (2) data：用于绘制的数据集。\n",
    "- (3) jitter：表示抖动的程度(仅沿类別轴)。当很多数据点重叠时，可以指定抖动的数量或者设为True使用默认值。\n",
    "为了让大家更好地理解，接下来，通过 stripplot()函数绘制一个散点图，示例代码如下。"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "998726c97d43c4f0"
  },
  {
   "cell_type": "code",
   "outputs": [
    {
     "data": {
      "text/plain": "<Axes: xlabel='day', ylabel='total_bill'>"
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "\n",
    "# 获取tips数据\n",
    "tips = sns.load_dataset(\"tips\")\n",
    "\n",
    "sns.stripplot(x=\"day\", y=\"total_bill\", data=tips)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-02-23T07:05:30.020406300Z",
     "start_time": "2024-02-23T07:05:29.040678200Z"
    }
   },
   "id": "7e856e93609f8425",
   "execution_count": 1
  },
  {
   "cell_type": "markdown",
   "source": [
    "从上图中可以看出，图表中的横坐标是分类的数据，而且一些数据点会互相重叠，不易于观察。为了解决这个问题，可以在调用striplot()函数时传入jitter参数，以调整横坐标的位置，改后的示例代码如下。"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "1374a8a08b0744b9"
  },
  {
   "cell_type": "code",
   "outputs": [
    {
     "data": {
      "text/plain": "<Axes: xlabel='day', ylabel='total_bill'>"
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.stripplot(x=\"day\", y=\"total_bill\", data=tips, jitter=True)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-02-23T07:06:13.344845500Z",
     "start_time": "2024-02-23T07:06:13.240585Z"
    }
   },
   "id": "1bbf4806926ba3ba",
   "execution_count": 2
  },
  {
   "cell_type": "markdown",
   "source": [
    "除此之外，还可调用 swarmplot0函数绘制散点图，该函数的好处是所有的数据点都不会重叠，可以很清晰地观察到数据的分布情况，示例代码如下。"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "537946124da12eb8"
  },
  {
   "cell_type": "code",
   "outputs": [
    {
     "data": {
      "text/plain": "<Axes: xlabel='day', ylabel='total_bill'>"
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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kAPCGVMulE4Ob8nAXPb52eyAa9tIL6ZggBTAAAG+YsGSD4YjKwOJ8XVcRNgxuxpeX6K26fb5/SLUbwDCFBABAG7NaeGG2qvStun1aPG5olvfMOwhgAMADqAHiL1Y5LVtZVWoLq5AAwOVi+RLUAPEPq6XxrCq1hwAGAFyOQpX+Y7U0nro/9pDECwAuN+KB1ar/4mjS9o457fTatPMd2CNkW5BXlZLECwA+QQ2Q4KHuT2pMIQGAyzGlACRjCgkAPCDIUwqwxy8r1ShkdwwBDADAL8yClFSVfb3EbgDj6BTShx9+qO9973saOnSoKisr9dhjjzW9VldXp+uuu05DhgzRZZddptWrVzu4pwCQfatqI5qwZINGPLBaE5ZsYJk04lgtpw/iSjXHApijR49q0qRJ+tKXvqQ//vGPuuuuu/TLX/5SL7zwgqLRqKZMmaKioiItXbpUY8eO1dSpU/Xxxx87tbsAkFWpar0Q3MAqSLGq7OtXjq1CikQiOvPMMzV79mx17txZp59+us4991ytW7dORUVFqqur09NPP61OnTqpd+/eeuONN7R06VLddNNNTu0yAGRNqifo5tMDseDGi9MDOM4qZ8XoNasgJYgr1WwFMGvXrrX9geXl5bbe161bN91///2SpGg0qvXr12vt2rWaNWuWqqurVVpaqk6dOjW9v6ysTBs3brS9HzGhxNR9H1tVG9HCNce/8NcP92YCFxBEmfTGWVxVpwv6cY57UWLOSiwonT+2VJJxwNqjoIO2761P+qxYUvetz9UkdaueeE7Yc/dBu/trK4C59tprbf7SkDZt2mTvNzczatQoffzxx7rgggt0ySWX6J577lG3bt3i3lNYWKidO3em/dmFhakTgfxg5bs7dctz8V/4W5+v0aPfLdMlA4sd3DMAdvQvzlf19n1J2/sVn6T3DZ6sJemDTw/ZSnaE+zzxdHXStqikJ9Z/LKOVJ1FJJ57QTqFQ/MuhkPSDr/bTxQOLlX9SR/1i1VbV7tqvvt3zNaWyty728fXfVgCzefPmrO7Egw8+qEgkotmzZ+vee+/V4cOHlZubG/ee3NxcNTQ0pP3Ze/YEYxXSAy+9n7QtGpUefOl9lXX37xAi4BfXlvXQ29v3JT1BX1t2qha+WWc4PXBG106KRIyDG7jbeyZB6fs7/2V6z9r1r3rNH1OqRWuaLac/J6xh3fMUiexXWfc8/ebfvxz3M178foRC9gYfbAUw6STPnnrqqbbfGzNo0CBJ0meffaZbbrlFV111lQ4fPhz3noaGBnXo0CHtz45GDYNZ37Eafg7Cnx/wupF9GnvjJNV66V2k6FHptucNpgeGhzm/PcoqZyUqmb42sk9RUv2foH4HbAUwo0aNUigUklnJmNhr6UwhRSIRbdy4URdddFHTtj59+ujzzz/XySefrG3btiW9P3FaCccFMYEL8Buz8vGxxn8UsvOPiRVhy6DU7DUcZyuAefnll1v9F2/fvl1Tp07Vq6++qu7du0uS3nnnHXXt2lVlZWVauHCh6uvrm0Zd1q1bp7KyslbfD7+wOhkAeJNfKqsiWaqglIA1Nccq8R45ckTf+ta3VFBQoDvuuEM7duzQ9OnTNWnSJH33u9/VmDFj1K9fP91444165ZVX9Mtf/lLLly9Pe4oqSJV4KTUeLNzc/M1PlVWBdLRqK4EzzzxTq1evVmFhoQYMGKCQxRqndFYh7dq1S3fffbfeeOMNdezYUd/97nc1efJkhUIhffjhh5oxY4aqq6vVs2dPTZ8+Xeedd57tz44JUgCD4ODm5n8TlmwwnBYeWJyvxeOGOrBHQNto1QCmqqpKw4YN04knnqiqqirL91ZUVNjfyzZAAAM/4ubmfyMeWK36L44mbe+Y006vTTvfgT0C2obdAMZWDkzzoCT234cOHdJHH32knJwclZSUqH379hnuKloLUwrBEcSy4UFDYn6wcT1PLe1eSPv379cdd9yhiooKff3rX9fll1+u8vJy3XPPPRnVaUHrSNVHBf7Sq8j4JsbNzT8mVoSVOFlPYn4wcD23J+1eSHfeeac++OADLVq0SKWlpYpGo6qurtbcuXN1+PBh3X333dnYT6RgVWqcqN1/WHXmT4lP3ePLS/RW3T5t23NQRXmNxT1nLt/ME7nPcT23J+1VSEOGDNHvfvc7lZaWxm3fuHGjrr/+eq1fv75Vd7ClgpIDw3x58LDqzF+sErMlkbQdIEG/nrdqDkxz3bt316effpq0/fDhwyooKEj349BKmC8PHrOiZ/Amq6duo2cwnsj9i+u5PWl3o77iiiv0ox/9SFOnTtWgQYN0wgkn6L333tP999+v6667Llv7iRSYUgC8LZN2ICRt+xPXc3tsTSENGDDA3odl2I06m4IyhSQxpQB4mdXSeLPeOCyb968gX89btQ5MJtatW6dBgwYldZVua0EKYAB416raiOFT9/yxpaa9ceaPLQ3MTQ3B4XgAM2zYMD333HMKh50d8iKAAeAVVk/dQX4iR7BkLYnXLodaLPkexY0Qw3fBf6wSszNJ2uY7Aj/L2gjM0KFD9fzzzzMC04pS9b/hYhUc9EJCKnxH4FWOj8Cg9Vkts5Ti60TEKjdysfInCl2hOaOHF74j3sYDaWpptxKAc6yWWaYKbuAv9EJCjFnZ+drdBwzfz3fE/WglYA8BjIdY9b/hhhYs9ELyn1W1EU1YskEjHlitCUs22L5ZmT28nNgusZNSI74j7scDqT0EMB5i1dyNG1qw0OjPX1ryxG328HLkaJTviEfxQGpP1gKYM844Qzk5Odn6+ECq7FukeWNKNbA4Xx1z2mlgcX5THQhuaMFi9V2A96R64rYanTF7eOl7cme+Ix7FA6k9tlYhPfvss7Y/8Otf/3oLdqf1+WkVUirUiQC8yap535zRA1KuPqTInb8E/Zi2aiG7UaNG2fylIb388su23ttWghTAAPCmlrYR4OHFf4J8TB2vxOsWBDAA3M7qiXvm8s2WozMstYXfZDWA+fTTT/XBBx/o6NHGkyoajaqhoUE1NTWaNGlS+nubRQQwALzA7InbbHQmXNBBdXvr47ZRqA5+kLUA5g9/+IPmzJmjL774QqFQqKllQCgU0pe//GX9/ve/z2yPs4QABoCXmY3OlBgEMBIdqr2EYnXG7AYwaa9CevTRR3XDDTfo7bffVmFhoV555RX96U9/0plnnqmvfvWrGe0sAMCY2Yqz3QcaDN/PUltvSLV0PtO6QEGSdiuBTz75RF//+teVm5urgQMHauPGjRo9erSmT5+uGTNm6Pvf/3429hMAAsuokWOvojzDqSWW2noDrWFaLu0ApmvXrvr0009VUlKiXr16adOmTRo9erS6d++uXbt2ZWMfASAQrKYUEl8rD3fRpp37k6aWqP3kDZm2hjELYII4HZX2FNLo0aP1ox/9SOvXr9eIESO0bNkyrVy5Uo888ohOO+20bOwjAPie1ZSC0WuPr92u8eUlFKrzqNZsDRPU3klpj8Dccsstys/P1z//+U9deOGFuuqqqzRr1iwVFBTo3nvvzcY+AoDvWT11G61DiEp6q24fCbsuZzYyMrEibJicPXF4WAvX1KU1PRjUzuNpBzAbN27U5MmTm9oE3Hzzzbr55pvV0NCg1157rdV3EACCwOqp22wlJQm77hYbGYlJzGWZN6bUcOl8NCrT4MZIUHsnpR3AjB8/Xn/729/UtWvXuO1btmzRD3/4Q7399tuttnMwFsS5TsDvrJJyzarxkrDrbqlGRoySsyVZBjdS8j3g5M65hkvq/f79sBXA/O53v9OcOXOa6r7827/9m+H7zjvvvFbdOSRLFdED8CarKYV0n8jhDqlGRlI9jEYlRaPH/x37mcR7gNT4fQja98N2Ibu1a9fq6NGjmjBhgh566CF16dLl+IeEQurYsaP69eun3NzcrO1sJvxWyM6qZwpz4YC3WfW/CXJvHK+yul5fVxE2bdIpyfS1RVXG+THhgg46qUOOL74fWavEu2PHDp166qkKhUI6cOCAjhw5EhfMuI3fAhirrrWvTTvfgT0C4DSmld3JqseVWaJuqgaeWyMHfX8PyGovpN/+9rd67LHHFIk0LtHq2rWrrrnmGk2dOjX9Pc0yvwUwqSJ6LmKAd2USiCROKUj0RHITs5Ezq4fRaFSmr51RaJwr5adR+Ky1EnjkkUf06KOPasqUKXr22We1bNky3XjjjVqyZIkWLFiQ0c7CvokVYYUStoUklZ/WJZB1AAC/yLS0fKqKrnCeUS6LVR0Yq9fM7gF+z3cxkvYIzMiRIzVr1iyNGjUqbvtf/vIXzZ07V6+88kqr7mBL+W0ERjKO6K2GI/0SlQN+lmm+xJ0rNvt+SsGrrEbHJOPE7PljS02TtmOFCv2eD2V3BCbtZdQHDhzQ6aefnrT9jDPO0KeffpruxyEDRkvvZi7fbPhev9cBAPwi09Ly9ERyL6vjtnjcUMul0lavGd0DgpgHlXYAM2TIEC1cuFBz5sxRu3aNM1BHjhzRb37zGw0aNKjVdxD2cBEDvM3qHN5qEdzMGT2AJdYulWoZtVkdmFSvJQpqeY20A5jp06dr3Lhxev311zVw4EBJ0rvvvquGhgY99thjrb6DsMeqhgQA98u0tHyqomdwjlVQ2pojJkFtJZB2Dswdd9yhm266SS+//LK2bt2q9u3b64wzztBXvvIV3XfffXrwwQezta8Z8WMOjBm/z4sCfmd2Dlstx+Ucdy+z4zahokSLq7bHvdfuyjGjwMdveVCtuox6w4YN+vDDDyU1BjAzZsxQ586d496zbds2Pfnkk1q/fn2Gu5wdQQpgAPgXDyjelMmiC7PRGbOk4B4FHbTdoJWAVxdxtGoAs3nzZk2ZMkXRaFQff/yxiouLm/JfGn9ZSJ06ddI111yj73znOy3b81ZGAAMAcBOrGjBzRg/IqArv9r31vhmhy1ohu2uvvVYPP/ywq6vvNue3AMZq3jSIWeh+xzEF/MdqyXymVXjnjB7gmxG6rFbi9RI/BTCpagpQjdNfqLCKliD4dS+rnKaZy83zWYJQhVfKYiVeOMcq05xqnP6T6piaVWYFUlX1hbNiK8cGFuerY047DSzOb5ruoQqvfWkvo4ZzrGoKmI0yUcjOu6yOd1DrPiCe2ShLUJfVeolZnRer5fQj+7BkvjkCGA+xqilgNm9KITvvsjre3KBgFcSmKqAG90qs61OUlyupsdp6LEj103RRSzCF5CFWw4cMLfqP1THlBuVP6UwLpmovYIQHGm+o7FukxeOGas7oAarbW6+6vfVMBRoggPEQq3lTq9fgTZnOk8Ob0s1bsQpieaDxB3IbrTGF5DGt1TsD3pDJPDm8Kd1pQaspRtoL+AMjrdYIYAAP4gblP6luVokJu+XhLtq0c79pEMsDjffRpNcaAQzgUdyg/CVV47/EhN1NO/drfHmJ3qrbRxDrE+kGqal+3u+1fyhkBwAuYFXcLFXvHHifWeFKu0Gqnwpf2i1kxwgMALiA1bTgzOWbDX+GXAj/MMuBeqtun60gNYilFQhgfCpoQ4mAH5hNC5IL4X8tTdgNYsIvAYwPUaU1GAhS/cfsmLLqzLvsnqfpBKlGnxnEIJccGB+y6nTKfLk/+Gm+G41SHdNVtRFWnXmMnWMaC0RO7pyrur31Se9NrOdllSvz+NrthjlUXvuekAMTYEEcSgyaIM53+52dYxqVFI0e/3c2McLXcqkK0TUPROr21iskqaSggyIHGwxbCFj1uXqrbl/gSisQwHiMnYtKEIcSg4Yg1XmtfYN3U/NOpqFbh9UxNQtETuqQo2lf6ZVRn6uglVaglYCH2C01Thlx/6OVgLPSLftvh9UxzVZJebPeS5Swbx1WxzST4IY+V/EcDWB27dqladOmqaKiQiNGjNC9996rzz77TJJUV1en6667TkOGDNFll12m1atXO7mrrpDqohK7GN25YrNKCjooXNCBvkg+RZDqLLvnolFTRrPXstW80+z3WQVhjPC1Dqtjmmlww7l/nGMBTDQa1bRp03T48GEtWbJEP//5z/XKK6/o/vvvVzQa1ZQpU1RUVKSlS5dq7Nixmjp1qj7++GOndtcV7Awxxy5GdXvrtX1vveaMHqDF44YSvPgMzTudlc652DwwsHot0+adqYIls9/HU372WR3TTIMbzv3jHFuFtHXrVl122WX629/+pqKixr/4P/3pT/rJT36iefPm6cYbb9Tf/vY3derUSZJ03XXXqaysTDfddFNav8dPq5CsVhdFJVYeAW0k03Mx0/PUrErvhIoSLa7aHvfe5qtcrPZza+Sg6r84mvRax5x2mjN6gGlV4CDeKLPFbGWZVVXmIPz9212F5NgIzMknn6zHHnusKXiJOXDggKqrq1VaWtoUvEhSWVmZNm7c2MZ76S4tHWK2elIDYF+m56Kdho1G56jZU3fVR/uSPqv5VJbV7+Mp3x2MVpbx92+PY6uQTjrpJI0YMaLp/48ePaonn3xS55xzjnbv3q1u3brFvb+wsFA7d+5M+/eEEq8yHnZBvyLNH1uqRWuaReznhFV5bIjZbOVRKGS+qmD+WFYVAOnK9Fw0G4HpVZinV7dYn6OhUPzNTrIOUEIh6xWJE4eHdetzBsXxzgkrFGr8M17Qj2tDtqS6Jgf579/ufds1y6jnz5+vmpoaPfPMM1q8eLFyc3PjXs/NzVVDQ0Pan1tYmHoYykuuLsrX1eeekbT9B1/tpxueXBc3XRYKNW4vKsrXE09XJ/1MVNIT6z82/DwA1jI5F6OS6WuPvLIl6bNi52j+SR11y3PxN7tbn69Rz66d9I89h5J+rl/xSSoqyrfcl4sHFiv/pI76xaqtqt21X32752tKZW9dPLA4k78OpCnVNXnluzv1i1e26P1dB9Sve2fdeEEfXcKxieOKAGb+/Pn67W9/q5///Ofq16+f2rdvr71798a9p6GhQR06dEj7s/fs8U8OTKJVtREtXHO8DsWE8hKt/Whf3BPhsO55ikT26z2DpzBJen/nvxSJGL8GIH1l3fM0f0zy6Myw7o1TNmavWZ2jD7z0ftL2aFQ6cuSoQlLSKMq1ZacqEtlvuS+x13/z71+O+1yuB23D6ng/88YHcQFr9fZ9uuGJdYEZMQ+F7A0+OB7A3H333Xrqqac0f/58XXLJJZKk7t27a8uW+KeRSCSSNK1kRzSa/YqVTjAafty0c39SoanYn91yWNuHfz+Ak0b2KUrKV4idZ2avWZ2jW02miiIHG4yrr/YuSvn74Cyr471wjfEKsUVr6siDacbROjAPP/ywnn76af3sZz/T5Zdf3rR98ODBevfdd1Vff7wvxLp16zR48GAndtOV0q1DUR7uQu0AwMVasqx28bihem3a+ZRM8JBs1f0JEscCmK1bt+oXv/iF/uM//kNlZWXavXt30z8VFRU65ZRTdMcdd6i2tlYLFizQ22+/rauvvtqp3XWddOtQPL52u8aXl5DVDrhUpjVD4E2Z1v3BcY7VgVmwYIF++tOfGr723nvv6cMPP9SMGTNUXV2tnj17avr06TrvvPPS/j1eqwNjt78KNWGAYKEbdXBQB8ZeHRjHApi24qUAprVar89cvtm0QNVr0843/L10nQW8hfPW34IcsBLAHOOlAMZqVOW6irBhcBNrvd78C271OYkjMKmCJgDuw3kLP7MbwDi+CgnHZdp6fdn3KuK2T6wIGw4/Gs2XWyUDcyEE3Kktz1tGetLD31fbIYBxkUyWUTYvQd78pBlfXqK36o7XhDk7XKCFa+o0c/nmuJOKbHegdbTmjSvVZ7XVeWtWLZaRHmNu+PsKUgDl6DJqxMt0GaXZqqPrKsJ6bdr5uq4irN+urTPsSEu2O9ByVl2fs/FZbXXepirXgHjplrdo7X50rfk99AICGBfJdBllqpPG6nWWZwIt15o3LjtBQzbOW6N9ZIQ2PemWt2hJkGv0fQpawMkUkstU9i0yHO6LBTdGWekzl282/KzYRcbqpLL6XAD22LlxxaSaVkj1WbHpgR4FHRSS4pL4o9HGxQBm0wdm0wtm+1hS0CFptaPECK0ZqzSAdPOW0j1W88aUBi7gJIDxELPgxuqksfO62ecCsKc1b1xmn1WUlxt349q+tz6pzIJVoGT1utk+SjLstcQIrTGrBRSpHjSby+RYLa6qS3mt9xumkHwg1XAy00RAdmVaFt5oKsDss4zYnSpO9brZPsZ6LVHB257Wqq6bybHatudgxtf6bOfmZAt1YHwisehR+WldVPXRvqbhx/Jwl7hVSUwTAa3LrPCYWV2msMH0TGxERVLSZ6UqUDnigdUZv35GofGTO9W7U7O76ied6rotOVbpFsBzY00h6sAEQDpzpEadqgG0HrOpWLNpBSOxp+zF44YmfVZLp4qtXr8ujdpROC6d/CajfEOz8hYtOVZm30Oz+4WXa4ExheRRVhntQctEB9zMbFph94EGw/c3r+2UTkf5lkwlW019wFy619rmncOtylu09rGyul94OfGXKSSPsmoXsDVyMK1eSADaXiatQxILVMZWHjXvkSYpqb1ITJD762SD1VTPnNEDLKeWUrV8aX6sivIaj+vuAw0ZFafzWvNfppB8zipqDlomOuBFVitWFq4xfrJ/q25f3E0lcQqjLmFlUiJWHLYuuyvGjKaWUo18xI5VOtNUZtNEVr9rzugBnp0+ZArJo6wy2tti1ZFXs9YBt7CaCrA7rM90sbMyXTEm2a+mbPcYW00TWf0uL08fMgLjoJb0rLB6ehvZJ7vF6dzQ7wPwg0xrO8V4OX/BD8wKgdqp+WJ0DZekf9V/rhEPrG66J7RGMJuqwa9XR+bIgXFIqqVrdoKbVEunW9rEy2wfUs3dArDP6DyTZGvJLeeiO9k9Lol5LkbL6nsUdNB2g2rIiZ+Vahm9l/Kf7ObAEMA4JJMEPqsRjtZey2/1eXeusK5HgbZnFfAGqTut11idZ5KSltyurdubUaCDtmVV86V50rWdB8PwsQAm8bMmVJTEPbDur//csO2DF4NZAphj3BrAtHZRqdZ+EvNa1nqQpboJuq1IFY5L50ndbqDj5ifrIDEa8YhGzc9HqwfDOaMHJI22L67anvReo7YPXgxmWYXkclZz3FtTzHkaPVHbbQBn9+ncr1nrXpRqBMVq7tsodvdKkaogaI38BqOidxIjb04zyiuZsGRD0vvs9DFK/Cyjz5GkkoIOOqlDTmCCWVYhOcRqpZBVxrhZpnms/kOi2HI+o8z0IGate43VMYqxugmS5Nm20l2dZ3clSrrH0c73Bm2vtfoYWfWuihXKWzxuqO+vyYzAOMQse31knyJFo8bz2lb1IWLvSadcudXTuV+z1r3GTplvqyc3s+k+agK1PjvdoBNHRMzOs/LTumjCkg1N7y3qnGuYyGl2HL1cHt7PUo2yJN4Tyk/rknargSAhB8alzDLGU1V+TKcBXDQq32St+1WqlQVS6oRBkjzbRqaJ+ZJS5jckPpzEtpklhZJo707pNHRMlffk5/OaHBiPy7Q+RFRSNHr83y15OmeUxXlWx6/5E32Pgg4KybiEfDZrAuE4q+mBdHJYzPIkwgb5DYlJobFRH7Olt4nfG3Jj2lbiKEusRUDiCIuUOu+J85oRGM8xi+AnVJQYPrWNLy/R42u383TuUWbHe3x5YyM4JWxndZFzWqs/mZ1Rt1S/02rprdF1gu9N20tV+iKd74Hf2B2BIYnXY8wSaKs+2pf03ljvFLOEW5Jx3c/sGK2t25v0XkrIOyvTxPykbWm81yqZM53rBN+btpeqRUA634OgYgTGJ4IcrQcRx9udzPLGrEZOE6tnS8Yjo+PLw0mF7BZV1aVVk4nvjXvYqZyb7gi5X6YHyYEJGLLSg4Xj7U5meWNmK0yaT+c0X7WU+N6zwwVxU4ax944vL9Gmnftt12Tie+MeqY6F2UrVaFRxK9RiQUoQe9QxAuMTmUTr8C6Ot/elUz071Qons1GfTHssIfsyaTdglTeT7micm9FK4JigBDDS8eHr2t0H1K5dSEeORNW3W2fPDiPCGsvcvS2d6Zx0p35oPeAN6bYbsApS0kkUdzumkAIoFqTc+nyNdKQxagvCMGJQsczd29KZzkl36ieT1gPIDqu8lHTbDVgt1Q/i9CCrkHwmVWZ7c+mWPQfQesxWLcWq8DY/L9MpMy+l33oA2ZFJS4dUQYqRXoV5aX9H/IAAxqPMgg+7Fy56pQDOMloiH6vTknheSkqr5AFLcN0hnQfKmEyDlCCWxWAKyYOsss3tDiPSKwVwnp0uw3amfhKnKcrDXdJanYTsSPVAmU5/rFiukt1+SUHACIwHWQUfdocRGWIG3MfqvDQbdTUaTX187XaNLy8J1NO4G1mNppiNgkuNo23hgg4KhRoTWksKOjQtRqnsW9TUcbpxBVryiF1QRtIJYDzI6iJndxiRIWbAfczOy6K8XNMpX7MHmrfq9jXd6BaPG0rw4gCrB8pU00t1e+sb+9pFG//bKDDJZIrKT5hC8iA7BZAShxAZYgbcz2z6wIidlSlwllkxupF9ijRz+WbDn0nV/LP5tT3ox54AxoPMLnJnhwtsV2jctHO/xpeX6K26fdSD8Cir5Zl+KSkeNGY3PKubXUuWz/I9yb7YA2Xs7zqWq1LUOde0Y/hWm4FJEJdON0chO49KLICUWGpc8meFRjRKVajMqsstsq+1A4NUlXitquua7UuqbshoPWZ/14m3pthxW7jG3jXbrxW5qcR7jF8DmERWF7hsVWjk6c05Vsc7KhGwOigbgUGqG5VVE8kglJ53O7PzNVzQQSd1yLHd/NOozUB5uIvvRtKpxOtyqW7+6QYH2arQaPfpjYq/bcvqeJsF7EGZF3daNkoUWOVSxF43+myrfQl6/kRbMvu7jhxs0LLvVSRtt2rkaJQOENTrLgGMA1Ld/DMJDqyCFLMh5lQJu1b7QR0ZZ1kdb7MRmKDMizstW4GBVesIswcNSs+7QyZ/1+m2GQjidZdl1A5ItfQt1etG9SCyUaGRpzf3sjreQSwp7iapan9Yte/IpL2HVVVtSs+7QzptI6xw3Y1HDowDUnWWtXp9zugBbdZl1mo/zig0fqJg/rztWHWjplO1c8zyF8aXh00T7e0k1ZqNsrQ0wZfvSdtI/LsuP62LFldtj3tPquMdlLwlkniPcWMAY3XBWTxuaFYSNDNZctuSCyPchYTrtmUUGKRaWZLqfDMLbu5csdnygYggxZ0yOd7jy0v0+Nrtvr/uEsAc48YAxs6KArPXZy43v1jNGT0g7eWSkvmSW0k8vfkAy2XdoSUjr1Yjnqw686ZMj3dj+wB/X3cJYI5xYwAjpR7iN3vdajleXUJRJDvLJVNd/AhSvCOTkTRucG2nJSOvVqUQ5owewGioBzlR+sIrCGCOcWsAkymz0ZkSgwBGSn0yRKMK9IniFXaW3Wc6xYC20ZKR11TTT80fNIryciVJuw80MF3oYi053n5nN4BhFZJLma1GMFtRtPtAg+HnxJZLGulVmEdTRw+wWmUSY7VijGPsDqlWA1q9nmrFUKxD8ZzRA1S3t151e+sD2Z3YS1pyvNGIOjAuZKcOTFSNXUpj/860Dkw0apznwoniHnZq7lgtrzSbYuAYtz2rWi5Wr6cqZBdDfSZvaenxDjoCGBdKVQfGKLgZX15i2l16ZB/rk4ETxd3s1H6wCmC5GLqb3RViiTe72Cht85+jToh/pAp2QQDjSlYXIbPg5q26fSlvUomjNjGcKO5mp4qnWYfy5lMMHGP3ybQlh9nP9SjoYNrhGPAbAhgXsrphWbVZN7tJ0bfI28yCk1gVz9gT+PjyEt81dfO7VFM+ZqMzZj8XUnKXY6YL4VcEMC5k9TRtlp0eK1OezsWOeXFvMJoCSqziGfSmbl5lNdpq9eBh1RyQ6UIEBcuoXcqs/orZ0rsJFSWmZalZRus/1HbxhlT5LZlW3aZ4HfyMZdQeF1sW+dq087V43NCUSy2rPtqX9Bkso/UvkjXdz87yd6vlslbHmGW2AFNInmSU6zJz+WbD97KM1p/sJPbCWXambq1WiLX2yjL6YcFvCGBcKt2LDctogyXVqiM4L9UoWeI5Pmf0gLhzPJOVZWbXDRL54UfkwLhQJs33UpUph//Qp8rdMu0unVjrJfEYR6NKu2mrVT80cmbgNvRCOsaLAUymCZpWib9mozkMKwPZkY1eN5kGKUFvDpgNLbmuttV116vXd08FMA0NDbryyit15513avjw4ZKkuro63Xnnndq4caNOPfVUTZ8+Xeefn/6J5sUAxqrNeroXG6sLnqS0R3oA2Gf2UJHpOZ5pB+MzCo2nmBmByUxLrquZjLC39j66/fpuN4BxPAfms88+03/913+ptra2aVs0GtWUKVPUr18/LV26VH/5y180depUrVixQqeeeqqDe9s2rPJZ0o2orRIJjeI66sN4h1efroLErLhkpue4VV5Npv3QkL6WXFfbqi5XEOp/ObqMesuWLfrWt76ljz76KG77m2++qbq6Os2ZM0e9e/fW5MmTNWTIEC1dutShPW1bZkskzw4XpFyWmcjqgsdSXO+ys0QX7mV2jpef1sXyuFqVRLBaWp2qEzbS05Lramtfd2M9sUY8sFoTlmxo+q4E4fru6AhMVVWVhg8frptvvllDhgxp2l5dXa3S0lJ16tSpaVtZWZk2btyY9u8IJZ7RHnBBvyLNH1uqRWuaDT2fE9bCN80j6gv6NQ5NLlxz/Mnt+uFhy6cys2JYvQrzPPn3FiRWT1cX9OOm5HaZnuPXDw/r1ucMRlLOCauyj/FnVh4LUi7oV8R3o5W05Lpq9bNm112ja7vV6rL5Y0sz+j1uYXf/HA1gvvOd7xhu3717t7p16xa3rbCwUDt37kz7dxQWpp5Hc6Ori/J19blnxG27c/l7hu/94NNDWrfroG55Lv6LfOvzNbrhK721aVd8HlAoJP3gq/0UlXTDk+sMX7Mz/wjnfLDnkPH2Tw9x7Dwik3P8iXU7lHNCO53YLqQj0agGnHKSplT21sUDi00/E63vB1/tZ3rtTHVdNfvZr/Tvpu89Xa33dx1Qv+6ddeMFfXTJwGKtfHen4bX90e+W6Yl1O5L2LSrpifUfW+6jX64RjufAGDl8+LByc3PjtuXm5qqhoSHtz9qzx3tJvGbOKOxkGFGf0bWTHnjp/aTt0aj02nufaP6Y5KeyYd0bh6LNXotEkn8P3MPqu8Cx8y6z41rYKUeTn1jX9P8NRxpHXq4ddirnqwPKuudlfF01+tny07rol69ubfr86u37dMMT65pWrCWKRqUHX3rftLnv+zv/ZbmPbv++hEL2Bh9cGcC0b99ee/fujdvW0NCgDh06pP1Z0ah8E8BYFbayqsQ7sk9R0lx37O/E6jW4l9V3gePnXWbH1UhU0qI1deSxOKQl19XE1ycs2ZD0+bHjm2nidjTq/+u7K3shde/eXZFIfDJiJBJJmlYKGqtEPPodBQtJmf5kdlx3HzAeffZTQmaQpQpSjKRK3A4CV47ADB48WAsWLFB9fX3TqMu6detUVlbm8J45z2xZJqXlg8fsuwBvMzqu9L7yt0yXwI/sE+w2Ma4cgamoqNApp5yiO+64Q7W1tVqwYIHefvttXX311U7vmmvxRA74V9CftP2uJUvgK/sWafG4oXpt2vlaPG5ooK75rqjEK0n9+/fX448/3lSJ98MPP9SMGTNUXV2tnj17avr06TrvvPPS/lwvVuIFgET0vvK3xON7drhAa+v2BrJQpadaCWQTAQz8ikq8gD95uQ1AayCAOcbrAYxbmoLBXYJ+gQP8LNOGvn5hN4BxZQ4MGqUqF2/ndaMS0/A+q0q8ALwtCG0AWgMBjIuluklZvU6vHH/jAgf4F2Ux7CGAcbGWNAXjCd3fuMAB/sWqM3sIYFws1U3K6nWe0P2NCxzgX5TFsMeVhezQKFVxOqvXF66po/CVj8UucCyr9R8S8yFRqNIOViG5XGJtgPLTuqjqo31NF7fycBe9Vbcv6Sa2qjZiGNwQxQPuxeoygGXUTbwewDSX6uKW+ORmFtwAcKegL58FJPsBDFNIHpIqMbd5cFOzc7827dzPkxvgIeSuAfYRwHhIpquOCGAAb7Bq6kduTLBwvFNjFZKHsOoI8Dez1WVnhwuo6xQg1PGyhwDGQ6yWzlIXBPA+s+Wza+v2Jr2Xuk7+RR0ve5hC8hCrpbPRqCyXXAPwBqPlszOXbzZ8LyOs/sSIuj0EMB5jVhuAuiCAf1nlxsB/ON72EMD4CIWPAH9KVdQS/sLxtoc6MADgAYlFLRlh9bcgH28K2R1DAAMAgHfYDWBYhQQAADyHAAYAAHgOSbyAR1GpE0CQkQMDeBBdiwH4FTkwgI9RqRNA0BHAAB5EpU4AQUcAA3gQva8ABB0BDOBBVo09ASAISOIFPCrIlToB+BeVeI8hgAEAwDtYhQQAAHyLAAYAAHgOAQwAAPAcAhgAAOA5BDAAAMBzCGAAAIDnEMAAAADPIYABAACeQwADAAA8hwAGAAB4DgEMAADwnBOd3gEAQGqraiNaVFWnbZGD6lWUp4kVYVX2pXkngotmjgDgcqtqI7r1+Zq4bSFJ88aUEsTAd2jmCAA+saiqLmlbVNJig+1AUBDAAIDLbYscNN6+x3g7EAQEMADgcr2K8oy3FxpvB4KAAAYAXG5iRVihhG0hSROHh53YHcAVSOIFAA9YVRvR4qo6bdtzUL0K8zRxeFgj+5DAC/+xm8RLAAMAAFyDVUgAAMC3CGAAAIDnEMAAAADPIYABAACeQwADAAA8hwAGAAB4DgEMAADwHAIYAADgOQQwAADAcwhgAACA5xDAAAAAzznR6R3ItlBiC1cAAOBadu/bvm/mCAAA/IcpJAAA4DkEMAAAwHMIYAAAgOcQwAAAAM8hgAEAAJ5DAAMAADyHAAYAAHgOAQwAAPAcAhgAAOA5vm8l4GW33367/vjHP5q+3qNHD1VUVOi+++5rw72CE0aNGqUdO3YkbR82bJieeuqpuG3bt2/XhRdeqJdfflklJSVttYtoBZ9//rkeffRRPfvss9q1a5eKiop0ySWX6KabblLnzp1T/vymTZt0+PBhDRs2rA32Fplq6XFGI1oJuNj+/ftVX18vSVqxYoUWLlyoZ555pun1++67Tzk5OQQwATBq1ChNmDBBl112Wdz2nJwcFRQUxG07cuSIPv30U3Xt2lUnnHBCG+4lWuree+/V66+/runTpyscDquurk5z585VSUmJHn300ZQ/P2rUKE2dOlVXXnllG+wtMtXS44xGjMC4WH5+vvLz85v++4QTTtDJJ5/c9HpOTo5TuwYH5Ofnxx1/M4nfE3jHH//4R91zzz0699xzJUklJSWaPXu2xo0bp08++UTdunVzeA/RGjjOrYMcGI87cOCAbr75Zg0ePFiVlZV64YUXml4bNWqUli1b1vT/a9asUf/+/SU1TjP0799fjzzyiMrLyzVnzpw233e0jmuvvVZ33323LrzwQlVWVuq9995T//79tX37dqd3DWkKhUJ68803dfTo0aZtQ4cO1fLly/WlL31Ju3bt0rRp01ReXq6zzjpL3/jGN7Ru3TpJjd+DHTt26I477tDtt9/u1B8BNqQ6znau3X/+85910UUXadCgQZo8ebL27t3b1n8MxxHAeNxLL72kgQMH6k9/+pNGjx6t6dOna//+/bZ/fv369Vq6dKnGjx+fxb1Eti1btkzz58/Xww8/rLy8PKd3BxkaP368nnjiCY0aNUqzZs3SypUrVV9frz59+ignJ0e33HKLjhw5oqefflrPPvusunfvrtmzZ0uSHnroIRUXF2v69OmaMWOGs38QWEp1nO149NFH9bOf/UxPPvmk/v73v2vRokVZ3mv3IYDxuKFDh+r73/++wuGwbrzxRjU0NGjbtm22f37ChAk67bTTdPrpp2dvJ9EqZs2apaFDh8b9c+jQIUlSZWWlhg0bprPOOsvhvURLTJkyRfPnz1dxcbH+8Ic/aNq0aRoxYoSWLl2qaDSqiy66SHfeead69+6tPn36aNy4cdqyZYskqaCgQCeccELc1DPcyeo42zVt2jR9+ctf1uDBg3XFFVfo73//exb32J3IgfG4cDjc9N+xi9Znn31m++d79OjR6vuE7Jg2bZouvvjiuG0dO3aUxHH0kzFjxmjMmDH65z//qdWrV+vJJ5/UjBkz1L9/f11zzTVasWKF1q9frw8++EDvvPNO3DQEvMPqONvRs2fPpv/u3LmzPv/882ztqmsxAuNxRqtMzBaWHTlyJGlb+/btW32fkB2FhYXq2bNn3D+hUEgSx9EPNm/eHLei8Etf+pKuuOIKPfHEEyouLtbrr7+u66+/XgsXLtSpp56q733ve5o3b56De4xMpDrOb775ZtLPGF27WcRBAONrOTk5OnjwYNP/19XVObg3AKwcOXJEixYtUk1NTdz23NxcdejQQZ06ddLatWu1ePFi3XDDDaqsrNQnn3wiyfyhBe6T6jh37dqVa7dNBDA+NmjQID3zzDN6//33tWbNGi1cuNDpXQJgYuDAgaqsrNSNN96oF154Qdu3b9fGjRs1a9YsNTQ06MILL1S7du20fPly7dixQy+++KIeeughSVJDQ4MkqVOnTtq2bVsgV6R4RarjfPHFF3PttokAxsf+8z//UyeddJKuvPJKzZ07Vz/4wQ+c3iUAFu6//36NHTtWDz/8sEaPHq3JkyfrwIEDevLJJ3XKKado9uzZ+vWvf62vfe1rWrBggWbOnKkTTzyx6Wn+mmuu0ZIlSzRz5kyH/ySwYnWcO3fuzLXbJirxAgAAz2EEBgAAeA4BDAAA8BwCGAAA4DkEMAAAwHMIYAAAgOcQwAAAAM8hgAEAAJ5DAAMAADyHAAaAqz300EO69tprnd4NAC5DAAMAADyHAAYAAHgOAQwAV9myZYuuueYaDR48WOPHj9c///nPptf+53/+R5deeqnOOussDR8+XHfddZeOHDmi//u//9OAAQP07rvvNr13z549Ki0t1YcffujEHwNAlhHAAHCNhoYGTZo0SeFwWMuWLdMll1yi3//+95Kkqqoq/fjHP9YPf/hDvfjii7rrrrv0zDPP6OWXX9Ypp5yisrIyrVy5sumzVq5cqTPPPFM9e/Z06o8DIIsIYAC4xuuvv669e/dq9uzZ6t27t8aNG6eLLrpIktSpUyfNnTtXF198sUpKSnTppZeqtLRUtbW1kqTLL79cL774YtNn/e///q8uv/xyR/4cALKPAAaAa2zZskWnn366OnXq1LRt0KBBkqSzzjpLAwYM0IMPPqhp06bpkksuUXV1tY4ePSpJuvTSS7Vjxw5t2rRJkUhE69ev12WXXebInwNA9hHAAHCVaDQa9/85OTmSpL/+9a+68sorFYlENGLECD344IMaNmxY0/u6du2qc889VytXrtSf//xnDR48WMXFxW267wDazolO7wAAxPTt21f/+Mc/tH//fuXn50uSNm3aJKkxgfeqq67SrFmzJElffPGFPvroI51zzjlNP/+1r31NixYtUnFxMdNHgM8xAgPANc477zydcsopmjFjhrZu3aply5ZpxYoVkqSCggJt2LBB7733nmpra3X77bdr9+7damhoaPr5iy66SP/4xz9UVVWlSy+91Kk/BoA2QAADwDVycnL0q1/9Svv27dM3vvENPfXUUxo3bpwkaerUqSosLNS///u/a+LEiWrfvr2uueaaphEaSercubO+8pWvaMiQISosLHTqjwGgDYSiiRPOAOBh3/72t/XNb35TV111ldO7AiCLyIEB4Atvvvmm1q9fr61btzJ9BAQAAQwAX3juuef08ssva86cOcrLy3N6dwBkGVNIAADAc0jiBQAAnkMAAwAAPIcABgAAeA4BDAAA8BwCGAAA4DkEMAAAwHMIYAAAgOcQwAAAAM/5/+F6Q+geoXtRAAAAAElFTkSuQmCC"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.swarmplot(x=\"day\", y=\"total_bill\", data=tips)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-02-23T07:06:46.404775100Z",
     "start_time": "2024-02-23T07:06:46.198088500Z"
    }
   },
   "id": "e5828aafa0e8670e",
   "execution_count": 3
  },
  {
   "cell_type": "markdown",
   "source": [
    "# 2 类别内的数据分布\n",
    "要想查看各个分类中的数据分布，显而易见，散点图是不满足需求的，原因是它不够直观。针对这种情况，我们可以绘制如下两种图形进行查看:\n",
    "\n",
    "- 箱形图:\n",
    "    - 箱形图（Box-plot）又称为盒须图、盒式图或箱线图，是一种用作显示一组数据分散情况资料的统计图。因形状如箱子而得名。\n",
    "    - 箱形图于1977年由美国著名统计学家约翰·图基（John Tukey）发明。它能显示出一组数据的最大值、最小值、中位数、及上下四分位数。\n",
    "- 小提琴图:\n",
    "    - 小提琴图 (Violin Plot) 用于显示数据分布及其概率密度。\n",
    "    - 这种图表结合了箱形图和密度图的特征，主要用来显示数据的分布形状。\n",
    "    - 中间的黑色粗条表示四分位数范围，从其延伸的幼细黑线代表 95% 置信区间，而白点则为中位数。\n",
    "    - 箱形图在数据显示方面受到限制，简单的设计往往隐藏了有关数据分布的重要细节。例如使用箱形图时，我们不能了解数据分布。虽然小提琴图可以显示更多详情，但它们也可能包含较多干扰信息。\n",
    "\n",
    "## 2.1 绘制箱形图\n",
    "seaborn中用于绘制箱形图的函数为 boxplot()，其语法格式如下:\n",
    "```python\n",
    "seaborn.boxplot(x=None, y=None, hue=None, data=None, orient=None, color=None,  saturation=0.75, width=0.8)\n",
    "```\n",
    "常用参数的含义如下:\n",
    "- (1) palette：用于设置不同级别色相的颜色变量。---- palette=[\"r\",\"g\",\"b\",\"y\"]\n",
    "- (2) saturation：用于设置数据显示的颜色饱和度。---- 使用小数表示\n",
    "使用 boxplot()函数绘制箱形图的具体示例如下。"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "f5b6f4f1056ee210"
  },
  {
   "cell_type": "code",
   "outputs": [
    {
     "data": {
      "text/plain": "<Axes: xlabel='day', ylabel='total_bill'>"
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x=\"day\", y=\"total_bill\", data=tips)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-02-23T07:36:15.039105600Z",
     "start_time": "2024-02-23T07:36:14.906253100Z"
    }
   },
   "id": "24615fa26de57dfc",
   "execution_count": 4
  },
  {
   "cell_type": "markdown",
   "source": [
    "上述示例中，使用 seaborn中内置的数据集tips绘制了一个箱形图，图中x轴的名称为day，其刻度范围是 Thur~Sun(周四至周日)，y轴的名称为 total_bill，刻度范围为10-50左右\n",
    "从图中可以看出，\n",
    "- Thur列大部分数据都小于30，不过有5个大于30的异常值，\n",
    "- Fri列中大部分数据都小于30，只有一个异常值大于40，\n",
    "- Sat一列中有3个大于40的异常值，\n",
    "- Sun列中有两个大于40的异常值\n",
    "## 2.2 绘制提琴图\n",
    "seaborn中用于绘制提琴图的函数为violinplot()，其语法格式如下\n",
    "```python\n",
    "seaborn.violinplot(x=None, y=None, hue=None, data=None)\n",
    "```\n",
    "通过violinplot()函数绘制提琴图的示例代码如下"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "1766e9e363eeaa0a"
  },
  {
   "cell_type": "code",
   "outputs": [
    {
     "data": {
      "text/plain": "<Axes: xlabel='day', ylabel='total_bill'>"
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.violinplot(x=\"day\", y=\"total_bill\", data=tips)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-02-23T07:44:53.247451500Z",
     "start_time": "2024-02-23T07:44:53.136789600Z"
    }
   },
   "id": "7f47343436c7e299",
   "execution_count": 5
  },
  {
   "cell_type": "markdown",
   "source": [
    "上述示例中，使用seaborn中内置的数据集绘制了一个提琴图，图中x轴的名称为day，y轴的名称为total_bill\n",
    "从图中可以看出，\n",
    "- Thur一列中位于5~25之间的数值较多，\n",
    "- Fri列中位于5-30之间的较多，\n",
    "- Sat-列中位于5-35之间的数值较多，\n",
    "- Sun一列中位于5-40之间的数值较多。\n",
    "# 3 类别内的统计估计\n",
    "要想查看每个分类的集中趋势，则可以使用条形图和点图进行展示。 Seaborn库中用于绘制这两种图表的具体函数如下\n",
    "\n",
    "barplot()函数：绘制条形图。\n",
    "pointplot()函数：绘制点图。\n",
    "这些函数的API与上面那些函数都是一样的，这里只讲解函数的应用，不再过多对函数的语法进行讲解了。\n",
    "## 3.1 绘制条形图\n",
    "最常用的查看集中趋势的图形就是条形图。默认情况下， barplot函数会在整个数据集上使用均值进行估计。若每个类别中有多个类别时(使用了hue参数)，则条形图可以使用引导来计算估计的置信区间(是指由样本统计量所构造的总体参数的估计区间)，并使用误差条来表示置信区间。\n",
    "使用 barplot()函数的示例如下"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "40435238916c72e5"
  },
  {
   "cell_type": "code",
   "outputs": [
    {
     "data": {
      "text/plain": "<Axes: xlabel='day', ylabel='total_bill'>"
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": "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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(x=\"day\", y=\"total_bill\", data=tips)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-02-23T07:52:51.256117200Z",
     "start_time": "2024-02-23T07:52:51.069317900Z"
    }
   },
   "id": "5b81cbfdc4503daf",
   "execution_count": 6
  },
  {
   "cell_type": "markdown",
   "source": [
    "## 3.2 绘制点图\n",
    "另外一种用于估计的图形是点图，可以调用 pointplot()函数进行绘制，该函数会用高度低计值对数据进行描述，而不是显示完整的条形，它只会绘制点估计和置信区间。\n",
    "通过 pointplot()函数绘制点图的示例如下。"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "db3c5ec0141b4bb7"
  },
  {
   "cell_type": "code",
   "outputs": [
    {
     "data": {
      "text/plain": "<Axes: xlabel='day', ylabel='total_bill'>"
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pointplot(x=\"day\", y=\"total_bill\", data=tips)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2024-02-23T08:01:51.526021800Z",
     "start_time": "2024-02-23T08:01:51.400970200Z"
    }
   },
   "id": "c8c6a50de00d8c89",
   "execution_count": 7
  },
  {
   "cell_type": "markdown",
   "source": [
    "# 4 小结\n",
    "- 类别散点图\n",
    "    - seaborn.stripplot()\n",
    "- 类别内的数据分布\n",
    "    - 箱线图\n",
    "        - seaborn.boxplot()\n",
    "    - 小提琴图\n",
    "        - seaborn.violinplot()\n",
    "- 类别内的统计估计\n",
    "    - 条形图\n",
    "        - barplot()\n",
    "    - 点图\n",
    "        - pointplot()"
   ],
   "metadata": {
    "collapsed": false
   },
   "id": "44d7dbfc53257bdf"
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
